1. Field of Invention
The present invention relates to a face recognition method, and more particularly to a hierarchical face recognition method performed according to facial angles in an image under detection.
2. Related Art
In recent years, human facial recognition systems have received great attention from research scholars and the industry, and computer devices (such as digital cameras and personal computers) have been deeply expected to have excellent performance on face recognitions of digital images. However, for a face recognition system of a computer device, different shooting angles result in wrong determinations of a face in an image under detection by the computer device.
A conventional face recognition flow may be divided into two parts, namely, training and recognition. In the training process of the conventional face recognition, a classification learning is performed on facial angles in all training samples one by one. For example, if the classification unit is 1 degree, the facial angles from 0 degree to 360 degrees are divided into 360 classification intervals. The computer device performs recognition training for each angle on all the training samples respectively.
The above problems not only appear in the process of the angle recognition training, but also appear in the recognition process of the facial angles. Still in the above example, since 1 degree is used as the classification interval in the training process, the facial angle recognition should also be performed 360 times on each of the recognition samples to find out the most appropriate result from 360 classification results. For example, in a learning of training/recognition performed on N classification intervals by M recognition samples, the complexity of the training/recognition for each angle is (M*N), which results in the following problems. That is, a long training time is required, and a large amount of memory space needs to be consumed. In this way, a lot of time is spent on other unnecessary facial angle determinations in the facial recognition process, and a lot of memory space and time is wasted.